Journal of Geotechnical Geology
Volume:14 Issue: 2, Summer and Autumn 2018

The Q-slope classification system is originally introduced by Barton and Bar (2017) for jointed rock-slope conditions description which is used for engineering judgment to evaluate slope stability. This study is attempted to use the Q-slope empirical classification system for assessment of jointed rock slopes stability in Bonab-Malekan highway project. To this end, 10 jointed slopes are observed in the high-way path which is required to investigate these slope stability conditions. According to the results of the stability analysis and sustainability possess based on Q-slope principle, a main part of the slopes are located in uncertain conditions (5 cases), 4 slopes is classified as stable and 1 slope indicate the failure condition and instability.

This study attempted to use the image processing techniques for estimating the discontinuity network detection in dimension stones from open-pit mining work front. The mentioned processing techniques are utilized to determine the discontinuities distribution of the rock mass as geometrical properties charging instability condition in excavation process in quarry. To evaluate the discontinuity network detection from quarry work front used image processing-based algorithm were run in Python programming languages. The algorithm, first of all, identifies the discontinuities and generates the network of discontinuities emplacements to model the rock body in quarry work front. To this end, the triple processing steps included pre-processing, main processing and post-processing are conducted to model. According to the results of computer-based simulation of discontinuity network, the used algorithm is capable to detect the discontinuities emplacements in rock mass and recognize the main rock block spatial distribution in quarry work front.

The presented study is attempted to investigate the landslide susceptibility of the Bonab city located in Urmia lake basin in East-Azerbaijan, NW of Iran. As methodology the coupled method contain analytical hierarchy process and fuzzy logic, named FAHP was applied to risk-ability evaluation and prepares sliding potential maps. For this purpose, three main triggering factors identified for the susceptibility assessment which is classified as geomorphology, geology and human activities where each class has several sub-classes. According to the landslide susceptibility assessment and zonation map, the main risk zone is located in east to southeast part on the Bonab city in Malekan-Bonab highway route.

The presented study attempted to investigate mechanical properties of concrete containing nanosilicates based on experimental uniaxial compressive strength test (UCS). For this purpose, different nanosilica dosages including 0%, 2%, 4% and 6% with considering the cement/water ratio are used to preparing the totally 10 mixing scheme and 30 concrete laboratory samples (10×10×10 cm cubic specimens) which is tested under 7, 28 and 90 days age. According to the experimental results by increasing the amount of nanosilica in the samples, UCS is increased and mechanical properties of concrete improved under loading. But in 6% nanosilica specimens incremental slope is get smooth then 4% nanosilica specimens. This was also observed for the 28-day and 90-day samples. In the meantime, some samples containing 6% nanosilica under uniaxial pressure experienced a resistance drop in strength features, indicating a decreasing trend of durability improvement at values above 6% nanosilica.

The present study attempt to investigate the soil permeability behavior in landfill liners, which is very valuable in controlling municipal waste leachate runaway. In this regard, laboratory experiment is conducted on 20 soil samples which are modified with 0%, 3%, 6% and 9% nanoclays, respectively. For this purpose, permeability test are performed for each case of samples with various nanocaly contents and obtained permeability results are compared. The nature of the utilized nanoclay, in this research, is of the mentomorillonite type. According to the results of the study, by increasing the nanoclay percentage from 0 to 9, the soil permeability reduces. The permeability in samples with 0% nanoclay reduces from 3.16×10 -4 cm/s to 4.09×10-7cm/s by increasing the naniclay percentage up to 9%. This value for acidic conditions made by leachate (pH = 6) is 2.12×10-5 cm/s; which also reduces to 6.22×10-7 cm/s by nanoclay ratio increasing with the same percentage. The obtained resultsrepresents the capability of nanoclays to controlling the municipal waste leachate runaway in landfill liners.

This paper is attempted to present the artificial intelligence based on algorithm which is used the image processing techniques for computer-based simulate of jointed rock slopes in three dimensional condition. For this purpose, the applying the digital image processing has been used for identifying of geometric structures in rock slope and preparing rock mass information. This information is used as a database for generating three dimensional models which is implemented in MATLAB software. The algorithm is utilized for processing input image; generate a main dataset and providing the 3D model of slope, based on geometrical properties and joint set’s network in rock slope. In this regard, several steps processing are conducted on input image that is concluded as pre-processing, main processing, feature extraction, database generation and model preparation. As results, the algorithm is able to generate simplified dataset for preparing the 3D view of the rock slope geometrical conditions.

Solar energy as the most important source of renewable energy is an important alternative to fossil and non-renewable energies which is highly related to the environmental changes. The power output delivered from a photovoltaic module depends on the amount of irradiance which reaches the solar cells. Many factors determine the ideal output or optimum yield in a photovoltaic module which can be classified to climatological, cosmological and geographical conditions. These environmental factors are directly affecting the performance losses in solar cells. The presented paper attempted to use the long short-term memory (LSTM) to evaluate the environmental parameters influencing on photovoltaic cells performance losses. According to the simulations, intensity and radiation angle, shadow, temperature, wind and air pressure are the main parameters which affect the solar cells functions and loss the performance.

The purpose of this study is application of fuzzy-based decision-making system (FMCDM) method and a device for monitoring and controlling water consumption in a smart house used for water supply management (WSM) based on intelligent water management system (IWMS). This paper presents an algorithm applied for water demand consumption (WDC) optimization in regular household and its capability to evaluate the WDC range and decision and controlled WSM in critical circumstances. For this purpose, the heuristic decision-making method are used to monitor and control the WCM as effective IWMS methods based on artificial intelligence technology (AIT) and smart-learning multi-sensor. To program the device software, the MATLAB fuzzy logic programming software has been used. In order to assess the device’s capability to respond to real conditions, a device is run to study sample-data for 24 hours a day for a month. In this study, four locations (kitchen, restroom, bathroom and garden balcony) are considered as the main WDC locations, then FMCDM algorithm are applied on these targets by main device. The results indicate that the first place (kitchen) has the greatest impact on WDC. However, the fourth place (garden balcony) has the lowest impact on WDC as well water consumption volume (WCV). Moreover, for analysis justification, the expert system (ES) is conducted as a comparison that shows the appropriate agreement with the FMCDM results.